Biodiversity data has been used extensively to approximate species population, track species status, or make conservation plans. However, complex information embedded in biodiversity data and information systems often makes it difficult to gain a holistic picture about the species, especially when geographic and historical information are involved. For instance, geographic information may be constantly changing, while in biodiversity data only the most recent geographic entities are documented. In legacy biodiversity literature, place-names that were used in the past may no longer be the same name used now. These challenges create a perpetual gap from linking historical texts that could be useful to understand species’ habitats and the causes of population reduction, to the actual species occurrence datasets that are used to inform decision-making.
In this study, we address these socio-geographic concerns in biodiversity data by proposing a conceptual model for historical sovereignties over time that consists of four phases: (1) collecting and preprocessing species and historical sovereignties data to determine geographic point of interests; (2) constructing taxonomies of the geographic entities and sovereignties based on certain time slices; (3) aligning taxonomies in a pairwise manner to compare each past year taxonomy with the most current year taxonomy; (4) producing Possible Worlds based on the alignments to demonstrate in a given past year, what was the historical sovereignty of a modern geographic entity. We hope this work can contribute to raising the awareness of the embedded assumptions in geographic information in biodiversity data; and to support multiple perspectives on geopolitical entities to shed light on how one might work with biodiversity data to make any decisions.
Related materials [link]
- Bishop, B. W., Moulaison, H. L., & Burwell, C. L. (2015). Geographic knowledge organization: Critical cartographic cataloging and place-names in the Geoweb. KO KNOWLEDGE ORGANIZATION, 42(4), 199-210.
- Boakes, E. H., McGowan, P. J., Fuller, R. A., Chang-qing, D., Clark, N. E., O’Connor, K., & Mace, G. M. (2010). Distorted views of biodiversity: spatial and temporal bias in species occurrence data. PLoS biology, 8(6).
- Bowker, G. C. (2000). Mapping biodiversity. International Journal of Geographical Information Science, 14(8), 739-754.
- Franz, N. M., & Sterner, B. W. (2018). To increase trust, change the social design behind aggregated biodiversity data. Database, 2018.
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